Overview

Brought to you by YData

Dataset statistics

Number of variables11
Number of observations200
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.2 KiB
Average record size in memory139.3 B

Variable types

Text1
Numeric10

Alerts

Area_km2 is highly overall correlated with Population_2020 and 3 other fieldsHigh correlation
CFR_% is highly overall correlated with Total_DeathsHigh correlation
Cases_per_Million is highly overall correlated with Cases_per_km2 and 4 other fieldsHigh correlation
Cases_per_km2 is highly overall correlated with Cases_per_Million and 3 other fieldsHigh correlation
Deaths_per_Million is highly overall correlated with Cases_per_Million and 4 other fieldsHigh correlation
Deaths_per_km2 is highly overall correlated with Cases_per_Million and 4 other fieldsHigh correlation
Population_2020 is highly overall correlated with Area_km2 and 2 other fieldsHigh correlation
Population_Density_Calc is highly overall correlated with Area_km2 and 1 other fieldsHigh correlation
Total_Cases is highly overall correlated with Area_km2 and 5 other fieldsHigh correlation
Total_Deaths is highly overall correlated with Area_km2 and 6 other fieldsHigh correlation
COUNTRY_REGION has unique values Unique
Total_Cases has unique values Unique
Population_2020 has unique values Unique
Area_km2 has unique values Unique
Cases_per_Million has unique values Unique
Cases_per_km2 has unique values Unique
Population_Density_Calc has unique values Unique
Total_Deaths has 20 (10.0%) zeros Zeros
Deaths_per_Million has 20 (10.0%) zeros Zeros
CFR_% has 20 (10.0%) zeros Zeros
Deaths_per_km2 has 20 (10.0%) zeros Zeros

Reproduction

Analysis started2025-08-19 13:21:48.660730
Analysis finished2025-08-19 13:21:58.462098
Duration9.8 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

COUNTRY_REGION
Text

Unique 

Distinct200
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
2025-08-19T16:21:58.697900image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length33
Median length29
Mean length9.64
Min length4

Characters and Unicode

Total characters1928
Distinct characters59
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique200 ?
Unique (%)100.0%

Sample

1st rowAfghanistan
2nd rowAlbania
3rd rowAlgeria
4th rowAndorra
5th rowAngola
ValueCountFrequency (%)
and 8
 
2.8%
republic 8
 
2.8%
islands 7
 
2.5%
of 6
 
2.1%
guinea 3
 
1.1%
new 3
 
1.1%
saint 3
 
1.1%
sudan 2
 
0.7%
state 2
 
0.7%
united 2
 
0.7%
Other values (235) 237
84.3%
2025-08-19T16:21:59.056815image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 283
14.7%
i 161
 
8.4%
n 151
 
7.8%
e 134
 
7.0%
r 108
 
5.6%
o 95
 
4.9%
81
 
4.2%
l 79
 
4.1%
t 74
 
3.8%
u 73
 
3.8%
Other values (49) 689
35.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1928
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 283
14.7%
i 161
 
8.4%
n 151
 
7.8%
e 134
 
7.0%
r 108
 
5.6%
o 95
 
4.9%
81
 
4.2%
l 79
 
4.1%
t 74
 
3.8%
u 73
 
3.8%
Other values (49) 689
35.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1928
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 283
14.7%
i 161
 
8.4%
n 151
 
7.8%
e 134
 
7.0%
r 108
 
5.6%
o 95
 
4.9%
81
 
4.2%
l 79
 
4.1%
t 74
 
3.8%
u 73
 
3.8%
Other values (49) 689
35.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1928
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 283
14.7%
i 161
 
8.4%
n 151
 
7.8%
e 134
 
7.0%
r 108
 
5.6%
o 95
 
4.9%
81
 
4.2%
l 79
 
4.1%
t 74
 
3.8%
u 73
 
3.8%
Other values (49) 689
35.7%

Total_Cases
Real number (ℝ)

High correlation  Unique 

Distinct200
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean356358.55
Minimum1
Maximum16256754
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2025-08-19T16:21:59.165532image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile35.75
Q12256
median23264.5
Q3156092.75
95-th percentile1341512.8
Maximum16256754
Range16256753
Interquartile range (IQR)153836.75

Descriptive statistics

Standard deviation1462498.6
Coefficient of variation (CV)4.1040088
Kurtosis80.793956
Mean356358.55
Median Absolute Deviation (MAD)23226
Skewness8.4307587
Sum71271710
Variance2.1389023 × 1012
MonotonicityNot monotonic
2025-08-19T16:21:59.291532image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49273 1
 
0.5%
48530 1
 
0.5%
92102 1
 
0.5%
7338 1
 
0.5%
16188 1
 
0.5%
10 1
 
0.5%
148 1
 
0.5%
1498160 1
 
0.5%
148682 1
 
0.5%
5049 1
 
0.5%
Other values (190) 190
95.0%
ValueCountFrequency (%)
1 1
0.5%
3 1
0.5%
4 1
0.5%
10 1
0.5%
13 1
0.5%
17 1
0.5%
19 1
0.5%
26 1
0.5%
27 1
0.5%
31 1
0.5%
ValueCountFrequency (%)
16256754 1
0.5%
9884100 1
0.5%
6901952 1
0.5%
2653928 1
0.5%
2376852 1
0.5%
1849403 1
0.5%
1843712 1
0.5%
1730575 1
0.5%
1498160 1
0.5%
1425774 1
0.5%

Total_Deaths
Real number (ℝ)

High correlation  Zeros 

Distinct168
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8048.915
Minimum0
Maximum299177
Zeros20
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2025-08-19T16:21:59.415914image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q144
median348.5
Q32607
95-th percentile41074.75
Maximum299177
Range299177
Interquartile range (IQR)2563

Descriptive statistics

Standard deviation29322.666
Coefficient of variation (CV)3.6430582
Kurtosis57.100473
Mean8048.915
Median Absolute Deviation (MAD)348.5
Skewness6.8996898
Sum1609783
Variance8.5981874 × 108
MonotonicityNot monotonic
2025-08-19T16:21:59.709295image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20
 
10.0%
2 4
 
2.0%
1 3
 
1.5%
44 3
 
1.5%
4 2
 
1.0%
7 2
 
1.0%
63 2
 
1.0%
79 2
 
1.0%
349 2
 
1.0%
25 2
 
1.0%
Other values (158) 158
79.0%
ValueCountFrequency (%)
0 20
10.0%
1 3
 
1.5%
2 4
 
2.0%
3 1
 
0.5%
4 2
 
1.0%
5 1
 
0.5%
6 1
 
0.5%
7 2
 
1.0%
8 1
 
0.5%
9 1
 
0.5%
ValueCountFrequency (%)
299177 1
0.5%
181402 1
0.5%
143355 1
0.5%
113953 1
0.5%
64520 1
0.5%
64170 1
0.5%
57911 1
0.5%
52196 1
0.5%
47624 1
0.5%
46941 1
0.5%

Population_2020
Real number (ℝ)

High correlation  Unique 

Distinct200
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37895780
Minimum520
Maximum1.4249298 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2025-08-19T16:21:59.822991image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum520
5-th percentile47473.7
Q11158030.2
median6867535
Q325875310
95-th percentile1.2528244 × 108
Maximum1.4249298 × 109
Range1.4249293 × 109
Interquartile range (IQR)24717280

Descriptive statistics

Standard deviation1.4604468 × 108
Coefficient of variation (CV)3.8538506
Kurtosis78.03092
Mean37895780
Median Absolute Deviation (MAD)6583987
Skewness8.5273813
Sum7.5791561 × 109
Variance2.1329048 × 1016
MonotonicityNot monotonic
2025-08-19T16:21:59.945110image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38972230 1
 
0.5%
2866849 1
 
0.5%
43451666 1
 
0.5%
77700 1
 
0.5%
33428485 1
 
0.5%
15585 1
 
0.5%
92664 1
 
0.5%
45036032 1
 
0.5%
2805608 1
 
0.5%
106585 1
 
0.5%
Other values (190) 190
95.0%
ValueCountFrequency (%)
520 1
0.5%
4500 1
0.5%
11655 1
0.5%
15585 1
0.5%
32709 1
0.5%
34007 1
0.5%
36922 1
0.5%
38756 1
0.5%
43413 1
0.5%
44276 1
0.5%
ValueCountFrequency (%)
1424929781 1
0.5%
1396387127 1
0.5%
335942003 1
0.5%
271857970 1
0.5%
227196741 1
0.5%
213196304 1
0.5%
208327405 1
0.5%
167420951 1
0.5%
145617329 1
0.5%
125998302 1
0.5%

Area_km2
Real number (ℝ)

High correlation  Unique 

Distinct200
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean656699.61
Minimum1
Maximum17098242
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2025-08-19T16:22:00.063601image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile159.1
Q116741.5
median109386.5
Q3483079.5
95-th percentile2176868.7
Maximum17098242
Range17098241
Interquartile range (IQR)466338

Descriptive statistics

Standard deviation1887858.9
Coefficient of variation (CV)2.8747678
Kurtosis37.533006
Mean656699.61
Median Absolute Deviation (MAD)108950.5
Skewness5.6757914
Sum1.3133992 × 108
Variance3.5640113 × 1012
MonotonicityNot monotonic
2025-08-19T16:22:00.185819image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
652230 1
 
0.5%
28748 1
 
0.5%
2381741 1
 
0.5%
468 1
 
0.5%
1246700 1
 
0.5%
91 1
 
0.5%
442 1
 
0.5%
2780400 1
 
0.5%
29743 1
 
0.5%
180 1
 
0.5%
Other values (190) 190
95.0%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
6 1
0.5%
54 1
0.5%
61 1
0.5%
78 1
0.5%
91 1
0.5%
102 1
0.5%
116 1
0.5%
142 1
0.5%
ValueCountFrequency (%)
17098242 1
0.5%
9984670 1
0.5%
9706961 1
0.5%
9372610 1
0.5%
8515767 1
0.5%
7692024 1
0.5%
3287590 1
0.5%
2780400 1
0.5%
2724900 1
0.5%
2381741 1
0.5%

Cases_per_Million
Real number (ℝ)

High correlation  Unique 

Distinct200
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14274.865
Minimum3.2083674
Maximum94440.154
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2025-08-19T16:22:00.303841image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum3.2083674
5-th percentile64.576408
Q1910.71337
median6649.3342
Q324706.16
95-th percentile50751.398
Maximum94440.154
Range94436.946
Interquartile range (IQR)23795.447

Descriptive statistics

Standard deviation17446.159
Coefficient of variation (CV)1.2221592
Kurtosis2.0520616
Mean14274.865
Median Absolute Deviation (MAD)6350.0299
Skewness1.4670459
Sum2854973.1
Variance3.0436845 × 108
MonotonicityNot monotonic
2025-08-19T16:22:00.421185image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1264.31051 1
 
0.5%
16927.99307 1
 
0.5%
2119.642547 1
 
0.5%
94440.15444 1
 
0.5%
484.2576623 1
 
0.5%
641.6426051 1
 
0.5%
1597.168264 1
 
0.5%
33265.80814 1
 
0.5%
52994.57373 1
 
0.5%
47370.64315 1
 
0.5%
Other values (190) 190
95.0%
ValueCountFrequency (%)
3.208367422 1
0.5%
5.601552805 1
0.5%
14.45441291 1
0.5%
21.89443589 1
0.5%
23.84624556 1
0.5%
24.59522766 1
0.5%
49.97707573 1
0.5%
59.27891765 1
0.5%
59.65519298 1
0.5%
64.52103308 1
0.5%
ValueCountFrequency (%)
94440.15444 1
0.5%
65855.06988 1
0.5%
65469.647 1
0.5%
60334.93765 1
0.5%
57252.91852 1
0.5%
55178.19707 1
0.5%
52994.57373 1
0.5%
52587.43143 1
0.5%
51728.93482 1
0.5%
51065.70279 1
0.5%

Deaths_per_Million
Real number (ℝ)

High correlation  Zeros 

Distinct181
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean243.01257
Minimum0
Maximum1552.6241
Zeros20
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2025-08-19T16:22:00.524449image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110.033745
median77.05809
Q3343.04641
95-th percentile913.09076
Maximum1552.6241
Range1552.6241
Interquartile range (IQR)333.01267

Descriptive statistics

Standard deviation325.05071
Coefficient of variation (CV)1.337588
Kurtosis2.0042662
Mean243.01257
Median Absolute Deviation (MAD)77.05809
Skewness1.5915991
Sum48602.514
Variance105657.96
MonotonicityNot monotonic
2025-08-19T16:22:00.638505image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20
 
10.0%
349.8614681 1
 
0.5%
59.74454466 1
 
0.5%
1016.731017 1
 
0.5%
50.57447316 1
 
0.5%
11.09831929 1
 
0.5%
43.16670983 1
 
0.5%
905.1863184 1
 
0.5%
892.141739 1
 
0.5%
431.5804288 1
 
0.5%
Other values (171) 171
85.5%
ValueCountFrequency (%)
0 20
10.0%
0.08183154045 1
 
0.5%
0.3621363291 1
 
0.5%
0.8205431175 1
 
0.5%
0.8394465562 1
 
0.5%
1.798405893 1
 
0.5%
2.172916336 1
 
0.5%
3.287629935 1
 
0.5%
3.29885396 1
 
0.5%
3.325777918 1
 
0.5%
ValueCountFrequency (%)
1552.624061 1
0.5%
1499.69124 1
0.5%
1101.254127 1
0.5%
1084.359196 1
0.5%
1016.731017 1
0.5%
1005.493498 1
0.5%
1005.30164 1
0.5%
1004.702824 1
0.5%
956.9117706 1
0.5%
925.2076153 1
0.5%

CFR_%
Real number (ℝ)

High correlation  Zeros 

Distinct181
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9843794
Minimum0
Maximum29.092655
Zeros20
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2025-08-19T16:22:00.753013image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.84023522
median1.6384453
Q32.534149
95-th percentile5.1749819
Maximum29.092655
Range29.092655
Interquartile range (IQR)1.6939138

Descriptive statistics

Standard deviation2.4530202
Coefficient of variation (CV)1.2361649
Kurtosis75.169555
Mean1.9843794
Median Absolute Deviation (MAD)0.81058154
Skewness7.1813049
Sum396.87588
Variance6.0173083
MonotonicityNot monotonic
2025-08-19T16:22:00.869859image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20
 
10.0%
2.066762827 1
 
0.5%
2.818614145 1
 
0.5%
1.076587626 1
 
0.5%
4.000162361 1
 
0.5%
2.291821102 1
 
0.5%
2.702702703 1
 
0.5%
2.721071181 1
 
0.5%
1.683458657 1
 
0.5%
0.9110714993 1
 
0.5%
Other values (171) 171
85.5%
ValueCountFrequency (%)
0 20
10.0%
0.04972565158 1
 
0.5%
0.1305483029 1
 
0.5%
0.1371742112 1
 
0.5%
0.1702598591 1
 
0.5%
0.2959763219 1
 
0.5%
0.2994011976 1
 
0.5%
0.3336054804 1
 
0.5%
0.3590664273 1
 
0.5%
0.3903839898 1
 
0.5%
ValueCountFrequency (%)
29.09265482 1
0.5%
9.11591912 1
0.5%
7.692307692 1
0.5%
6.865073475 1
0.5%
6.756756757 1
0.5%
6.298513046 1
0.5%
6.128440367 1
0.5%
5.762711864 1
0.5%
5.691959696 1
0.5%
5.651320096 1
0.5%

Cases_per_km2
Real number (ℝ)

High correlation  Unique 

Distinct200
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.1680199
Minimum8.7715816 × 10-6
Maximum334
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2025-08-19T16:22:00.982402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum8.7715816 × 10-6
5-th percentile0.0020791171
Q10.051493543
median0.40196858
Q32.597376
95-th percentile17.363938
Maximum334
Range333.99999
Interquartile range (IQR)2.5458825

Descriptive statistics

Standard deviation28.814119
Coefficient of variation (CV)4.6715347
Kurtosis91.859498
Mean6.1680199
Median Absolute Deviation (MAD)0.39441652
Skewness8.9726068
Sum1233.604
Variance830.25345
MonotonicityNot monotonic
2025-08-19T16:22:01.104381image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.07554543643 1
 
0.5%
1.688117434 1
 
0.5%
0.03867003171 1
 
0.5%
15.67948718 1
 
0.5%
0.01298467955 1
 
0.5%
0.1098901099 1
 
0.5%
0.334841629 1
 
0.5%
0.5388289455 1
 
0.5%
4.998890495 1
 
0.5%
28.05 1
 
0.5%
Other values (190) 190
95.0%
ValueCountFrequency (%)
8.771581553 × 10-61
0.5%
8.204118467 × 10-51
0.5%
0.0001731418919 1
0.5%
0.0005830791952 1
0.5%
0.000588316722 1
0.5%
0.001378504673 1
0.5%
0.00156641604 1
0.5%
0.001782162589 1
0.5%
0.001938088829 1
0.5%
0.001983041953 1
0.5%
ValueCountFrequency (%)
334 1
0.5%
179.1666667 1
0.5%
116.5267974 1
0.5%
82.14084507 1
0.5%
44.56 1
0.5%
35.12974684 1
0.5%
31.91803279 1
0.5%
28.05 1
0.5%
26 1
0.5%
19.91617531 1
0.5%

Deaths_per_km2
Real number (ℝ)

High correlation  Zeros 

Distinct180
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.050290699
Minimum0
Maximum1
Zeros20
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2025-08-19T16:22:01.223813image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.00068937681
median0.0067007493
Q30.040675777
95-th percentile0.21617749
Maximum1
Range1
Interquartile range (IQR)0.039986401

Descriptive statistics

Standard deviation0.13151959
Coefficient of variation (CV)2.6151872
Kurtosis27.12385
Mean0.050290699
Median Absolute Deviation (MAD)0.0067007493
Skewness4.8939361
Sum10.05814
Variance0.017297403
MonotonicityNot monotonic
2025-08-19T16:22:01.347547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20
 
10.0%
0.1666666667 2
 
1.0%
0.003021940113 1
 
0.5%
0.03488938361 1
 
0.5%
0.1688034188 1
 
0.5%
0.001089958984 1
 
0.5%
0.009049773756 1
 
0.5%
0.0002975856261 1
 
0.5%
0.08415425478 1
 
0.5%
0.2555555556 1
 
0.5%
Other values (170) 170
85.0%
ValueCountFrequency (%)
0 20
10.0%
3.759398496 × 10-61
 
0.5%
1.728459079 × 10-51
 
0.5%
3.592728318 × 10-51
 
0.5%
6.314127861 × 10-51
 
0.5%
6.357388316 × 10-51
 
0.5%
7.943925234 × 10-51
 
0.5%
9.243271822 × 10-51
 
0.5%
0.000100041146 1
 
0.5%
0.0001011261926 1
 
0.5%
ValueCountFrequency (%)
1 1
0.5%
0.8360655738 1
0.5%
0.8333333333 1
0.5%
0.5880175577 1
0.5%
0.5253164557 1
0.5%
0.4549019608 1
0.5%
0.275862069 1
0.5%
0.2641827913 1
0.5%
0.2555555556 1
0.5%
0.2397610514 1
0.5%

Population_Density_Calc
Real number (ℝ)

High correlation  Unique 

Distinct200
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean332.08103
Minimum0.025865086
Maximum18461
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2025-08-19T16:22:01.462194image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.025865086
5-th percentile4.3361143
Q131.871185
median88.487237
Q3226.20178
95-th percentile660.38826
Maximum18461
Range18460.974
Interquartile range (IQR)194.3306

Descriptive statistics

Standard deviation1483.9638
Coefficient of variation (CV)4.46868
Kurtosis117.41488
Mean332.08103
Median Absolute Deviation (MAD)63.394814
Skewness10.26739
Sum66416.206
Variance2202148.7
MonotonicityNot monotonic
2025-08-19T16:22:01.582225image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59.75228064 1
 
0.5%
99.72342424 1
 
0.5%
18.24365706 1
 
0.5%
166.025641 1
 
0.5%
26.81357584 1
 
0.5%
171.2637363 1
 
0.5%
209.6470588 1
 
0.5%
16.19768091 1
 
0.5%
94.32834617 1
 
0.5%
592.1388889 1
 
0.5%
Other values (190) 190
95.0%
ValueCountFrequency (%)
0.02586508569 1
0.5%
2.090406015 1
0.5%
2.106204167 1
0.5%
3.014841058 1
0.5%
3.337229707 1
0.5%
3.559893204 1
0.5%
3.705683067 1
0.5%
3.708450986 1
0.5%
3.781637246 1
0.5%
3.794687756 1
0.5%
ValueCountFrequency (%)
18461 1
0.5%
8323.759155 1
0.5%
5451.5 1
0.5%
1931.332026 1
0.5%
1714.793333 1
0.5%
1630.876582 1
0.5%
1185.759259 1
0.5%
1134.518879 1
0.5%
933.7844828 1
0.5%
805.0512821 1
0.5%

Interactions

2025-08-19T16:21:57.327688image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:48.993414image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:49.936379image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:50.834221image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:51.731504image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:52.794156image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:53.630412image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:54.532266image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:55.382822image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:56.424014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:57.418138image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:49.099396image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:50.032454image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-08-19T16:21:55.214801image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:56.249249image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:57.115139image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:58.137100image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:49.834701image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:50.741962image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:51.637120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:52.706971image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:53.540769image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:54.437356image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:55.294493image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:56.334206image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-19T16:21:57.237168image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-08-19T16:22:01.670497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Area_km2CFR_%Cases_per_MillionCases_per_km2Deaths_per_MillionDeaths_per_km2Population_2020Population_Density_CalcTotal_CasesTotal_Deaths
Area_km21.0000.352-0.180-0.4240.025-0.2510.817-0.5780.5180.565
CFR_%0.3521.0000.036-0.0070.4230.2940.396-0.1140.3070.504
Cases_per_Million-0.1800.0361.0000.8580.8780.798-0.0990.1550.5990.525
Cases_per_km2-0.424-0.0070.8581.0000.7210.909-0.1180.6040.4790.401
Deaths_per_Million0.0250.4230.8780.7211.0000.8460.1060.0430.6890.705
Deaths_per_km2-0.2510.2940.7980.9090.8461.0000.0340.4980.5620.547
Population_20200.8170.396-0.099-0.1180.1060.0341.000-0.1000.6890.720
Population_Density_Calc-0.578-0.1140.1550.6040.0430.498-0.1001.000-0.020-0.060
Total_Cases0.5180.3070.5990.4790.6890.5620.689-0.0201.0000.964
Total_Deaths0.5650.5040.5250.4010.7050.5470.720-0.0600.9641.000

Missing values

2025-08-19T16:21:58.273025image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-08-19T16:21:58.384881image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

COUNTRY_REGIONTotal_CasesTotal_DeathsPopulation_2020Area_km2Cases_per_MillionDeaths_per_MillionCFR_%Cases_per_km2Deaths_per_km2Population_Density_Calc
0Afghanistan49273.01971.0389722306522301264.31051050.5744734.0001620.0755450.00302259.752281
1Albania48530.01003.028668492874816927.993068349.8614682.0667631.6881170.03488999.723424
2Algeria92102.02596.04345166623817412119.64254759.7445452.8186140.0386700.00109018.243657
3Andorra7338.079.07770046894440.1544401016.7310171.07658815.6794870.168803166.025641
4Angola16188.0371.0334284851246700484.25766211.0983192.2918210.0129850.00029826.813576
5Anguilla10.00.01558591641.6426050.0000000.0000000.1098900.000000171.263736
6Antigua and Barbuda148.04.0926644421597.16826443.1667102.7027030.3348420.009050209.647059
7Argentina1498160.040766.045036032278040033265.808142905.1863182.7210710.5388290.01466216.197681
8Armenia148682.02503.028056082974352994.573725892.1417391.6834594.9988900.08415494.328346
9Aruba5049.046.010658518047370.643149431.5804290.91107128.0500000.255556592.138889
COUNTRY_REGIONTotal_CasesTotal_DeathsPopulation_2020Area_km2Cases_per_MillionDeaths_per_MillionCFR_%Cases_per_km2Deaths_per_km2Population_Density_Calc
190Viet Nam1397.035.09664868533121214.4544130.3621362.5053690.0042180.000106291.803090
191Yemen2083.0606.03228404652796864.52103318.77088129.0926550.0039450.00114861.147732
192France2376852.057911.06448005355169536861.818336898.1227112.4364584.3082720.104969116.876269
193Marshall Islands4.00.04341318192.1383000.0000000.0000000.0220990.000000239.850829
194Nicaragua5887.0162.06755895130373871.38713723.9790582.7518260.0451550.00124351.819740
195Poland1135676.022864.03842836631267929553.065046594.9771582.0132503.6320830.073123122.900374
196Slovenia96314.01459.021176412027345481.741239688.9741931.5148374.7508510.071968104.456223
197Virgin Islands, U.S.1807.023.010044234717990.482069228.9878741.2728285.2074930.066282289.458213
198Western Sahara766.01.05560482660001377.5789141.7984060.1305480.0028800.0000042.090406
199Zambia18274.0367.018927715752612965.46255119.3895572.0083180.0242810.00048825.149366